Posted
by
Soulskill
on Tuesday January 29, 2013 @07:18PM
from the i-would-use-it-to-play-quake dept.

coondoggie writes "Stanford researchers said this week they had used a supercomputer with 1,572,864 compute cores to predict the noise generated by a supersonic jet engine. 'Computational fluid dynamics simulations test all aspects of a supercomputer. The waves propagating throughout the simulation require a carefully orchestrated balance between computation, memory and communication. Supercomputers like Sequoia divvy up the complex math into smaller parts so they can be computed simultaneously. The more cores you have, the faster and more complex the calculations can be. And yet, despite the additional computing horsepower, the difficulty of the calculations only becomes more challenging with more cores. At the one-million-core level, previously innocuous parts of the computer code can suddenly become bottlenecks.'"

Most of these CFD problems are time marching problems, governed by hyperbolic differential equations. Basically the state of fluid at some point X, at time t, is influenced only by the state of the fluid prior to that time. So when they are marching from t to t+delta(t), only the solution at the previous time step matters. Even in space, only a small region at T-Delta(t) affects any give point at T. Such problems are inherently parallel in data dependency. Such problems lend themselves for parallelism. This is not to minimize what they have achieved. If it was that easy, they would have done it long time ago. Physics governed by elliptical (and to some extent parabolic) equations are not that lucky.